journal article·2015-09

Laminated collagen-fiber bio-composites for soft-tissue bio-mimetics

Mirit Sharabi, Dafna Benayahu, Yehuda Benayahu, Jessica Isaacs, Rami Haj-Ali

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Abstract

Abstract The objective of this study was to introduce a class of collagen-fiber reinforced bio-composite laminates as biomimetic of soft tissues. These novel all-natural bio-composite laminates include long collagen fibers from soft coral embedded in an alginate hydrogel matrix. Controlling the fiber orientation and volume fraction enabled the fabrication of laminates with wide range of mechanical behaviors. Four material systems were investigated in the current study having different fiber orientations: longitudinal (0°), transverse (90°), cross-plied (0/90°) and angle-plied (±30°). The range of Fiber volume fractions (FVFs) for the laminated membranes is between 0.21 and 0.31. The laminates were subjected to uniaxial loading, yielding hyperelastic stress–strain behavior. A hyperelastic finite element (FE) model was constructed for the heterogeneous laminate, based on the fiber and matrix hyperelastic material behavior and their FVF, in order to predict the overall bio-composite mechanical behavior. The predictions of the FE model were verified from the tested laminated systems. The FE model consisted of beam elements representing the collagen fibers embedded in the solid matrix (alginate). Good predictions were demonstrated by the proposed FE model compared with the tested bio-composites for all orientations up to 10% strain. The overall hyperelastic stress–strain behavior was in a similar range to known native soft tissues. In addition, the model allowed for examining the mechanical behavior of laminates with other FVFs. The new bio-composite material can be used for future soft tissue mimicry and repair.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Elasticity and Material Modeling · Mechanical Behavior of Composites · Cellular and Composite Structures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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